Pavement Performance Prediction of Semarang–Solo Toll Road, Indonesia, using Markov Chain Model

Authors

  • Hulfa Istikomah Diponegoro University
  • Bagus Hario Setiadji Diponegoro University
  • Bambang Riyanto Diponegoro University

DOI:

https://doi.org/10.9744/ced.27.1.12-21

Keywords:

pavement performance, prediction, Markov-Chain

Abstract

Roads are one of the infrastructures that significantly impact a country's economic growth. The condition of the roads usually decreases due to increasing vehicle volumes. Predicting road conditions is essential for planning future maintenance. This study aims to evaluate the pavement conditions over five years using Markov chain model for five sections of the Semarang-Solo toll road, Indonesia.  Two scenarios are selected in the simulation, without-handling and with-handling programs. The results show that the historical data used to compile the transition probability matrix (TPM) from the Markov model greatly influences the simulation results in both scenarios. In addition, the simulation results also indicate that the inner lane for all segments of Semarang - Solo direction is the most crucial because these segments have a relatively high rate of decline in road steadiness and a shorter cycle time for implementing the handling program.

References

Ministry of Public Works and Public Housing, Strategic Plan of the Directorate General of Highways, 2020, pp. 1–414, retrieved from https://drive.google.com/file/d/1o9biHDBLw5w3MqvGhZNYWfUjyWpg9e1z/view. (in Bahasa Indonesia).

Trans Marga Jawa Tengah, Traffic Volume Data, Semarang, 2021 (unpublished, in Bahasa Indonesia).

Ministry of Public Works and Public Housing, Minimum Service Standards for Toll Roads. Regulation of the Minister of Public Works of the Republic of Indonesia Number 16/PRT/M/2014 2014 (in Bahasa Indonesia).

Pérez-Acebo, H., Isasa, M., Gurrutxaga, I., García, H., and Insausti, A., International Roughness Index (IRI) Prediction Models for Freeways, Transportation Resesearch Procedia. 71, 2023, pp. 292–9. doi: https://doi.org/10.1016/j.trpro.2023.11.087

Sazali, A., Setiadji, B.H., and Haryadi, B., Application of the Markov Chain Model in Road Management in West Bangka District, Rekayasa, 12(2), 2019, pp. 141–50. doi: https://doi.org/10.21107/rekayasa.v12i2.5907. (in Bahasa Indonesia).

Yamany, M.S., Abraham, D.M., and Labi, S., Comparative Analysis of Markovian Methodologies for Modeling Infrastructure System Performance, Journal of Infrastructure System, 27(2), 2021. doi: https://doi.org/10.1061/(ASCE)IS.1943-555X.0000604

Abaza, K.A., Empirical Markovian-based Models for Rehabilitated Pavement Performance used in a Life Cycle Analysis Approach, Structure and Infrastruct Engineering, 13(5), 2016, pp. 625–36. doi: https://www.tandfonline.com/doi/abs/10.1080/15732479.2016.1187180

Panthi, K., A Methodological Framework for Modeling Pavement Maintenance Costs for Projects with Performance-based Contracts, Florida International University; 2009.

Pérez-Acebo, H., Bejan, S., and Gonzalo-Orden, H., Transition Probability Matrices for Flexible Pavement Deterioration Models with Half-Year Cycle Time, International Journal of Civil Engineering, 16(9), 2018, pp.1045–56. doi: https://link.springer.com/article/10.1007/s40999-017-0254-z

Ministry of Public Works, Procedures for Road Maintenance and Inspection, Regulation of the Minister of Public Works of the Republic of Indonesia Number 13/PRT/M/2011 Republik Indonesia; 2011 pp. 1–28 (in Bahasa Indonesia).

Ortiz-García, J.J., Costello, S.B., and Snaith, M.S., Derivation of Transition Probability Matrices for Pavement Deterioration Modeling, Journal of Transportaion Engineering, 132(2), 2006, pp. 141–61. doi: https://doi.org/10.1061/(ASCE)0733-947X(2006)132:2(141)

Abaza, K.A., Simplified Staged-homogenous Markov Model for Flexible Pavement Performance Prediction, Road Materials and Pavement Design, 17(2), 2016, pp. 365–81. doi: https://www.tandfonline.com/doi/abs/10.1080/14680629.2015.1083464

Abaza, K.A. and Ashur, S.A., Optimum Decision Policy for Management of Pavement Maintenance and Rehabilitation, Transportation Research Report, 1655(1), 1999, pp. 8–15. doi: https://journals.sagepub.com/doi/10.3141/1655-02

Widiarto, R.I., Setiadji, B.H., and Haryadi, B., Relationship between Slope and Ramp Length on Toll Road Traffic Accidents, Media Komunikasi Teknik Sipil, 28(2), 2023, pp. 192–201. doi: https://doi.org/10.14710/mkts.v28i2.43665. (in Bahasa Indonesia).

Sazali, A., Setiadji, B.H., and Haryadi, B., Prediction of Road Handling Cost using Markov Chain Method in Regency Road Network, International Journal Integrated Engineering, 13(4), 2021, pp. 275–83. doi: https://doi.org/10.30880/ijie.2021.13.04.026

Wei, B., Guo, C., and Deng, M., An Innovation of the Markov Probability Model for Predicting the Remaining Service Life of Civil Airport Rigid Pavements, Materials, 15(17), 2022, 6082. doi: https://doi.org/10.3390/ma15176082

Lee, D.G. and Russell, J.S., Panel Data Analysis of Factors Affecting As-built Roughness of Asphaltic Concrete Pavements, Journal of Transportation Engineering, 130(4), 2004, pp. 479–85. doi: https://doi.org/10.1061/(ASCE)0733-947X(2004)130:4(479)

Kaloop, M.R., El-Badawy, S.M., Hu, J.W., and Abd El-Hakim, R.T., International Roughness Index Prediction for Flexible Pavements using Novel Machine Learning Techniques, Engineering Application of Artificial Intelligence, 122(2023), 2023;122:106007. doi: https://doi.org/10.1016/j.engappai.2023.106007

Downloads

Published

2025-03-21

How to Cite

Istikomah, H., Setiadji, B. H., & Riyanto, B. (2025). Pavement Performance Prediction of Semarang–Solo Toll Road, Indonesia, using Markov Chain Model. Civil Engineering Dimension, 27(1), 12–21. https://doi.org/10.9744/ced.27.1.12-21

Issue

Vol. 27 No. 1 (2025): MARCH 2025

Section

Articles

License

Copyright (c) 2025 Hulfa Istikomah, Bagus Hario Setiadji, Bambang Riyanto

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

Authors who publish with this journal agree to the following terms:
  1. Authors retain the copyright and publishing right, and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
  2. Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
  3. Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) followingthe publication of the article, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See The Effect of Open Access).